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01 October 2019 | Story Nikile Ntsababa (Registrar)

The nomination process for the election of two representatives to serve on the UFS Council was finalised on Tuesday, 17 September 2019 – the closing date for nominations.
 
Here are the names of the nominees (listed alphabetically):
 
Representative from the Qwaqwa Campus:
None
 
Other representative:
Mr Christo Dippenaar
Dr Pieter du Toit
Mr Lefa Mabaso
Dr Walter Matli
Mr Zama Sigwebela
 
Please note that no nominations were received for representatives from the Qwaqwa Campus.  Since this scenario is not legislated in the Statute, Institutional Rules, and Convocation Constitution, the Registrar will, after consultation with the President of the Convocation, open another round of nominations for Qwaqwa representatives to Council (with the closing date 8 October 2019) to ensure that the campus is also represented on Council.
 
Convocation and Alumni members from the Qwaqwa Campus are therefore given a second opportunity to nominate one representative from among their members for the Qwaqwa Campus.  All nominations must reach the office of the Registrar no later than 16:30 on Wednesday, 9 October 2019.
 
Every nomination form  shall be signed by four (4) members of the Convocation and shall contain the written acceptance of the nomination by the nominee under his/her signature as well as an abridged CV and a motivation of more or less 200 words.
 
Nominations are to be submitted to:  email: registrar@ufs.ac.za or delivered by hand to Nikile Ntsababa, Main Building, Room 51, Bloemfontein Campus.
 
Kindly take note that late or incomplete nominations will not be accepted or considered.
 
Further information regarding the election process will follow in due course.

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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